Effect of Ferromagnetic Material Composition on Magnetic Flux Leakage Signal Behavior During Carbon Steel Cyclic Testing

Fatigue cracks in steel structures pose a significant risk of failure if not detected early or managed properly. Metal Magnetic Memory (MMM) testing, which relies on detecting variations in the self-magnetic leakage field (SMLF), is a commonly applied non-destructive technique for crack detection and monitoring. However, a limited understanding of how SMLF evolves under cyclic loading conditions presents a challenge in improving the reliability of MMM testing. To enhance the precision of fatigue crack detection in steel structures, it is essential to explore the relationship between SMLF behaviour and loading conditions. In particular, studying how differences in ferromagnetic material composition affect MMM signals can provide valuable insights for improving structural health monitoring. This research focuses on examining MMM signal responses during fatigue crack propagation in carbon steels with varying ferromagnetic compositions. The study also aims to correlate these MMM responses with crack dimensions. A constant amplitude cyclic loading approach was applied, and an MMM scanning instrument was used to measure the SMLF signals. Three types of pre-cracked carbon steel specimens: ASSAB 705, ASSAB 709 and ASSAB 760, were tested at stress ratios (R) of 0.1 and 0.3. SMLF data were then assessed in correspondence with the quantified ferromagnetic content in each material. The findings demonstrate that the constants in the fitted exponential model differ based on the ferromagnetic composition of the steel, highlighting the influence of material properties on MMM signal characteristics.